Description

Usage

1

Arguments

noInst

Number of instances to generate.

classNoise

Proportion of randomly determined values in the class variable.

Details

Problem is
described by six important and two
irrelevant features. The important features correspond to different
feature types from the marketing theory: two basic features
(B_{weak} and B_{strong}), two performance features (P_{weak}
and P_{strong}), two excitement features (E_{weak} and
E_{strong}), and two irrelevant features (I_{uniform} and
I_{normal}). The values of all features are randomly generated
integer values from 1 to 5, indicating for example score assigned to
each of the features by the survey's respondent. The dependent
variable for each instance (class) is the sum of its features'
effects, which we scale to the uniform distribution of integers 1-5,
indicating, for example, an overall score assigned by the respondent.